|
|
|
| Registros recuperados: 20 | |
|
| |
|
| |
|
| |
|
| |
|
| |
|
|
| Trostel, Philip A.. |
| This study estimates marginal rates of return to investment in schooling in 12 countries. Significant systematic nonlinearity in the marginal rate of return is found. In particular, the marginal rate of return is increasing significantly at low levels of education, and decreasing significantly at high levels of education. This may help explain why estimates of the return to schooling are often considerably higher when instrumenting for education. |
| Tipo: Journal Article |
Palavras-chave: Return to education; Nonlinearity; Instrumental variables; I20; J24. |
| Ano: 2005 |
URL: http://purl.umn.edu/37550 |
| |
|
| |
|
| |
|
| |
|
| |
|
|
| Key, Nigel D.; McBride, William D.. |
| Estimating how the use of production contracts affects farm productivity is difficult when unobservable factors are correlated with both the decision to contract and productivity. To account for potential selection bias, this study uses the local availability of production contracts as an instrument for whether a farm uses a contract in order to estimate the impact of contract use on total factor productivity. Results indicate that use of a production contract is associated with a large increase in productivity for feeder-to-finish hog farms in the United States. The instrumental variable method makes it credible to assert that the observed association is a causal relationship rather than simply a correlation. |
| Tipo: Journal Article |
Palavras-chave: Productivity; Production contracts; Instrumental variables; Sample selection; Productivity Analysis. |
| Ano: 2008 |
URL: http://purl.umn.edu/45659 |
| |
|
| |
|
| |
|
|
| Poi, Brian P.. |
| The two-stage least-squares (2SLS) instrumental variables estimator is commonly used to address endogeneity. However, the estimator suffers from bias that is exacerbated when the instruments are only weakly correlated with the endogenous variables and when many instruments are used. In this article, I discuss jackknife instrumental variables estimation as an alternative to 2SLS. Monte Carlo simulations comparing the jackknife instrument variables estimators to 2SLS and limited information maximum likelihood (LIML) show that two of the four variants perform remarkably well even when 2SLS does not. In a weak-instrument experiment, the two best performing jackknife estimators also outperform LIML. |
| Tipo: Journal Article |
Palavras-chave: Jive; 2SLS; LIML; JIVE; Instrumental variables; Endogeneity; Weak instruments; Research Methods/ Statistical Methods. |
| Ano: 2006 |
URL: http://purl.umn.edu/117586 |
| |
|
| |
|
| |
|
|
| Fisher, Monica G.. |
| Research shows households are more likely to be poor in rural versus urban America. Does this phenomenon partly reflect that people who choose rural residence have unmeasured attributes related to human impoverishment? To address this, two models are estimated using Panel Study of Income Dynamics data. A single equation Probit model of household poverty replicates the well-documented finding of higher poverty risk in rural places. However, a two-stage instrumental variables approach accounting for residential choice finds no measured effect of rural location on poverty. Results suggest failure to correct for endogenous rural residence leads to over-estimation of the "rural effect". |
| Tipo: Working or Discussion Paper |
Palavras-chave: Endogeneity; Households; Instrumental variables; Poverty; Rural; Food Security and Poverty. |
| Ano: 2004 |
URL: http://purl.umn.edu/18917 |
| |
|
| |
|
|
| Fisher, Monica G.. |
| Includes: On the Empirical Finding of a Higher Risk of Poverty in Rural Areas: Is Rural Residence Endogenous to Poverty?:COMMENT, by Thomas A. Hirschl; On the Empirical Finding of a Higher Risk of Poverty in Rural Areas: Is Rural Residence Endogenous to Poverty?: REPLY, by Monica Fisher. Research shows people are more likely to be poor in rural versus urban America. Does this phenomenon partly reflect that people who choose rural residence have unmeasured attributes related to human impoverishment? To address this question, two models are estimated using Panel Study of Income Dynamics data. A single equation Probit model of individual poverty replicates the well-documented finding of higher poverty risk in rural places. However, an instrumental variables... |
| Tipo: Journal Article |
Palavras-chave: Endogeneity; Instrumental variables; Omitted variable bias; Poverty; Rural; Food Security and Poverty. |
| Ano: 2005 |
URL: http://purl.umn.edu/31219 |
| |
| Registros recuperados: 20 | |
|
|
|
